How to evaluate a conversational AI platform: use cases and features

Benefits of conversational AI

In our previous article [link] we delved into the topic of conversational AI and the many benefits of using a platform empowered by this innovative technology. We explored how the ability to naturally understand and respond to human conversations, added to the ability to generate new and original content, can revolutionize interactions between companies and their customers, ensuring a unique Customer Experience.

Conversational AI, in fact, not only improves the accuracy and relevance of the responses provided by virtual assistants, but also enables the creation of more engaging and personalized experiences: it reduces response time to customer inquiries by increasing Customer Satisfaction and is also able to handle much of the interaction autonomously, freeing up valuable human resources to devote to more complex strategic tasks.

Generative AI, on the other hand, produces original content from existing data. This technology has the ability to answer questions outside common domains in creative and innovative ways, demonstrating ahigh ability to learn and generate new ideas.

Through conversational AI, therefore, more fluid and complex answers can be provided, tailored to the specific needs of users. This enables companies to answer complex questions with technologies such as chatbots and virtual assistants by understanding, processing and responding to a wide range of voice and text inputs, enabling personalized and natural interaction with users in different languages.

The use cases of Conversational AI

The many use cases of conversational AI in business processes and customer interactions can be grouped into the following four application areas:

1. Informative

Conversational AI responds to customer requests or offers guidance on specific topics. For example, users can ask service chatbots about the weather, details about a product, or specific instructions. Another example is virtual assistants that answer questions with real-time information about world news. In addition, if a company has a large knowledge base available (e.g., in the form of FAQs), this can be used as input for AI to automatically answer customer questions.

2. Data acquisition

Conversational AI tools can be used to collect data or feedback from users. For example, human-like interactions can be created during a customer onboarding process. Another interesting scenario is post-purchase or post-service chats, where feedback is collected on the customer journey in terms of experiences, preferences or areas of dissatisfaction and building personalized experiences.

3. Transactions

Conversational AI facilitates activities that require interactions. For example, customers can use advanced chatbots to place orders on e-commerce platforms, purchase tickets or make reservations. Some financial institutions use these chatbots to enable users to check account balances, transfer money or pay bills.

4. Assistance

Conversational AI applications can send alerts to users about upcoming appointments, remind them of unfinished tasks, or suggest products based on browsing behavior. Virtual assistants can proactively contact website visitors and offer assistance or provide updates on shipping or service disruptions, without the customer having to wait for an operator and offering 24-hour customer support across time zones.

What is a conversational AI platform

A conversational AI platform is advanced software that facilitates the creation, training, and maintenance of tools such as chatbots, voice bots, and virtual assistants. These technologies automate customer interactions and improve service quality, increasing the operational efficiency of companies.

By integrating conversational capabilities with generative AI engines, these platforms can create interactive, intelligent assistants capable of large-scale natural language conversations. Through training, they recognize and respond to a wide range of inputs, tailoring responses to users' needs.

As a result, companies can offer more efficient and personalized customer service, reducing operational costs and increasing customer satisfaction. By automating answers to frequently asked questions and handling complex inquiries without operator intervention, organizations can allocate human resources to strategic, high value-added activities.

In addition, conversational AI platforms continuously improve through machine learning: virtual assistants collect data during interactions, optimizing their performance by adapting to customer needs, ensuring increasingly accurate and relevant responses.

How to Evaluate a Conversational AI Platform.

In order to evaluate a Conversational AI Platform that is suitable for business needs, it is important to delve into its features and check its ability to ensure high performance and scalability. The following is a list of essential features that should always be analyzed:

• Omnichannel support: must support major communication channels such as web chat, SMS/text, and social media and integrate seamlessly with these channels to ensure a consistent and seamless user experience;
• Ease of configuration: should enable operators to easily update and manage requests and content, ensuring consistency with changing business needs at all times;
• Building a Customer Journey: must be able to handle very complex CJs through simple no-code configurations;
• Natural Language Processing: must correctly handle the intent of the request and process responses enabling smooth and natural conversations;
• Contextualized responses: must ensure consistent responses by pre-configuring dialogue paths and accessing the preloaded knowledge base;
• Learning ability: must be able to learn correctly from user interactions;
• High reliability: must demonstrate effectiveness and reliability of the underlying technology, on the algorithms and data sets to scale the implementation by demonstrating it with case studies or references;
• Languages adapted to the relevant Industry: must be familiar with the jargon and terminology of a particular industry and thus be able to be trained with company-specific knowledge bases;
• Dialogue scripting: can entirely transcribe the conversations to be analyzed, assessing user sentiment and context;
• Unified experience: must offer a seamless experience, capable of handling multiple bots and providing conditional responses based on user characteristics, ensuring personalized interactions for different target segments;
• Rapid switch to human assistants: The best conversational AI platforms are able to switch to human assistant support in real time when needed;
• Integration with CRM and Knowledge Base: must be able to access the company's knowledge bases to produce customized information enabling a richer and more accurate user experience;
• Customizable Analytics: must be able to track relevant metrics enabling evidence-based decision making, adapting to ever-changing business objectives.

These elements, combined, make it possible to offer a product that not only meets but exceeds the expectations of end customers, paving the way for a future in which artificial intelligence will be increasingly integrated into enterprise systems.

Learn more about the capabilities of our Inxide conversational AI platform or see it in action, fill out the form or write to us at marketing@increso.it